Min and max operations for multiplication and/or division under the simple interval system

ABSTRACT

One embodiment of the present invention provides a system for performing a minimum computation for an interval multiplication operation. This system receives four floating-point numbers, including a first floating-point number, a second floating-point number, a third floating-point number and a fourth floating-point number. The system then computes a minimum of the four floating-point numbers, wherein if the four floating-point numbers include one or more default NaN (not-a-number) values, the system sets the minimum to negative infinity. One embodiment of the present invention provides a system for performing a minimum computation for an interval division operation. This system receives four floating-point numbers, including a first floating-point number, a second floating-point number, a third floating-point number and a fourth floating-point number. The system then computes a minimum of the four floating-point numbers, wherein if the four floating-point numbers include one or more default NaN (not-a-number) values, the default NaN values are ignored in computing the minimum.

RELATED APPLICATION

[0001] The subject matter of this application is related to the subjectmatter in a pending non-provisional application by the same inventor asthe instant application and filed on 26 Mar. 2001, entitled, “Minimumand Maximum Operations to Facilitate Interval Multiplication and/orInterval Division,” Ser. No. 09/818,021 (Attorney Docket No.SUN-P5608-SPL).

BACKGROUND

[0002] 1. Field of the Invention

[0003] The present invention relates to performing arithmetic operationson interval operands within a computer system. More specifically, thepresent invention relates to a method and an apparatus for performingminimum and maximum operations to facilitate interval multiplicationand/or interval division operations in the “simple” interval system.

[0004] 2. Related Art

[0005] Rapid advances in computing technology make it possible toperform trillions of computational operations each second. Thistremendous computational speed makes it practical to performcomputationally intensive tasks as diverse as predicting the weather andoptimizing the design of an aircraft engine. Such computational tasksare typically performed using machine-representable floating-pointnumbers to approximate values of real numbers. (For example, see theInstitute of Electrical and Electronics Engineers (IEEE) standard 754for binary floating-point numbers.)

[0006] In spite of their limitations, floating-point numbers aregenerally used to perform most computational tasks.

[0007] One limitation is that machine-representable floating-pointnumbers have a fixed-size word length, which limits their accuracy. Notethat a floating-point number is typically encoded using a 32, 64 or128-bit binary number, which means that there are only 2³², 2⁶⁴ or 2¹²⁸possible symbols that can be used to specify a floating-point number.Hence, most real number values can only be approximated with acorresponding floating-point number. This creates estimation errors thatcan be magnified through even a few computations, thereby adverselyaffecting the accuracy of a computation.

[0008] A related limitation is that floating-point numbers contain noinformation about their accuracy. Most measured data values include someamount of error that arises from the measurement process itself. Thiserror can often be quantified as an accuracy parameter, which cansubsequently be used to determine the accuracy of a computation.However, floating-point numbers are not designed to keep track ofaccuracy information, whether from input data measurement errors ormachine rounding errors. Hence, it is not possible to determine theaccuracy of a computation by merely examining the floating-point numberthat results from the computation.

[0009] Interval arithmetic has been developed to solve theabove-described problems. Interval arithmetic represents numbers asintervals specified by a first (left) endpoint and a second (right)endpoint. For example, the interval [a, b], where a<b, is a closed,bounded subset of the real numbers, R, which includes a and b as well asall real numbers between a and b. Arithmetic operations on intervaloperands (interval arithmetic) are defined so that interval resultsalways contain the entire set of possible values. The result is amathematical system for rigorously bounding numerical errors from allsources, including measurement data errors, machine rounding errors andtheir interactions. (Note that the first endpoint normally contains the“infimum”, which is the largest number that is less than or equal toeach of a given set of real numbers. Similarly, the second endpointnormally contains the “supremum”, which is the smallest number that isgreater than or equal to each of the given set of real numbers.)

[0010] However, computer systems are presently not designed toefficiently handle intervals and interval computations. Consequently,performing interval operations on a typical computer system can behundreds of times slower than performing conventional floating-pointoperations. In addition, without a special representation for intervals,interval arithmetic operations fail to produce results that are asnarrow as possible.

[0011] What is needed is a method and an apparatus for efficientlyperforming arithmetic operations on intervals with results that are asnarrow as possible. (Interval results that are as narrow as possible aresaid to be “sharp”.)

[0012] One performance problem occurs during minimum and maximumcomputations for interval multiplication and interval divisionoperations. For example, the result of multiplying two intervals,[a,b]×[c,d]=[min(ac,ac,bc,bd), max(ac,ad,bc,bd)] (with appropriaterounding).

[0013] During these minimum and maximum computations, many special casesarise. For example, the minimum and maximum computations must deal withspecial cases for empty intervals, underflow conditions and overflowconditions.

[0014] These special cases are presently handled through computer codethat includes numerous “if” statements to detect the special cases.Unfortunately, this code for dealing with special cases can occupy alarge amount of memory. This makes it impractical to insert the code forthe minimum and maximum operations “inline”—as opposed to calling afunction to perform the min-max operation. Moreover, executing the codefor dealing with special cases can be time-consuming, thereby degradingcomputational performance.

[0015] What is needed is a method and apparatus for efficientlyperforming minimum and maximum operations for interval multiplicationand/or interval division operations.

SUMMARY

[0016] One embodiment of the present invention provides a system forperforming a minimum computation for an interval multiplicationoperation. This system receives four floating-point numbers, including afirst floating-point number, a second floating-point number, a thirdfloating-point number and a fourth floating-point number. The systemthen computes a minimum of the four floating-point numbers, wherein ifthe four floating-point numbers include one or more default NaN(not-a-number) values, the system sets the minimum to negative infinity.

[0017] In one embodiment of the present invention, the minimum is a leftendpoint of a resulting interval from the interval multiplicationoperation. In this embodiment: the first floating-point number is theresult of a multiplication operation between the left endpoint of afirst interval and the left endpoint of a second interval; the secondfloating-point number is the result of a multiplication operationbetween the left endpoint of the first interval and the right endpointof the second interval; the third floating-point number is the result ofa multiplication operation between the right endpoint of the firstinterval and the left endpoint of the second interval; and the fourthfloating-point number is the result of a multiplication operationbetween the right endpoint of the first interval and the right endpointof the second interval.

[0018] In one embodiment of the present invention, computing the minimuminvolves setting the minimum to a value representing the empty interval,if any of the four floating-point numbers contain the value representingthe empty interval. In a variation on this embodiment, the valuerepresenting the empty interval is a non-default NaN value.

[0019] In one embodiment of the present invention, if none of the fourfloating-point numbers is a default NaN value or a value representingthe empty interval, computing the minimum involves selecting the minimumof the four floating-point numbers.

[0020] One embodiment of the present invention provides a system forperforming a maximum computation for an interval multiplicationoperation, comprising. This system receives four floating-point numbers,including a first floating-point number, a second floating-point number,a third floating-point number and a fourth floating-point number. Thesystem then computes a maximum of the four floating-point numbers,wherein if the four floating-point numbers include one or more defaultNaN (not-a-number) values, the system sets the maximum to positiveinfinity.

[0021] In one embodiment of the present invention, the maximum is aright endpoint of a resulting interval from the interval multiplicationoperation.

[0022] In one embodiment of the present invention, computing the maximuminvolves setting the maximum to a value representing the empty interval,if any of the four floating-point numbers contain the value representingthe empty interval.

[0023] In one embodiment of the present invention, if none of the fourfloating-point numbers is a default NaN value or a value representingthe empty interval, computing the maximum involves selecting the maximumof the four floating-point numbers.

[0024] One embodiment of the present invention provides a system forperforming a minimum computation for an interval division operation.This system receives four floating-point numbers, including a firstfloating-point number, a second floating-point number, a thirdfloating-point number and a fourth floating-point number. The systemthen computes a minimum of the four floating-point numbers, wherein ifthe four floating-point numbers include one or more default NaN(not-a-number) values, the default NaN values are ignored in computingthe minimum.

[0025] In one embodiment of the present invention, the firstfloating-point number is the result of a division operation between theleft endpoint of a first interval and the left endpoint of a secondinterval; the second floating-point number is the result of a divisionoperation between the left endpoint of the first interval and the rightendpoint of the second interval; the third floating-point number is theresult of a division operation between the right endpoint of the firstinterval and the left endpoint of the second interval; and the fourthfloating-point number is the result of a division operation between theright endpoint of the first interval and the right endpoint of thesecond interval.

[0026] In one embodiment of the present invention, computing the minimuminvolves setting the minimum to negative infinity, if the secondinterval contains zero.

[0027] One embodiment of the present invention provides a system forperforming a maximum computation for an interval division operation.This system receives four floating-point numbers, including a firstfloating-point number, a second floating-point number, a thirdfloating-point number and a fourth floating-point number. The systemthen computes a maximum of the four floating-point numbers, wherein ifthe four floating-point numbers include one or more default NaN(not-a-number) values, the default NaN values are ignored in computingthe maximum.

[0028] In one embodiment of the present invention, computing the maximuminvolves setting the maximum to positive infinity, if the secondinterval contains zero.

BRIEF DESCRIPTION OF THE FIGURES

[0029]FIG. 1 illustrates a computer system in accordance with anembodiment of the present invention.

[0030]FIG. 2 illustrates the process of compiling and using code forinterval computations in accordance with an embodiment of the presentinvention.

[0031]FIG. 3 illustrates an arithmetic unit for interval computations inaccordance with an embodiment of the present invention.

[0032]FIG. 4 is a flow chart illustrating the process of performing aninterval computation in accordance with an embodiment of the presentinvention.

[0033]FIG. 5 illustrates four different interval operations inaccordance with an embodiment of the present invention.

[0034]FIG. 6 illustrates the “Full” system for representing intervalsusing two floating-point numbers in accordance with an embodiment of thepresent invention.

[0035] Table 1A lists the possible arguments to the minimum and maximumoperations and corresponding results for an interval multiplicationoperation in accordance with an embodiment of the present invention.

[0036] Table 1B lists the possible arguments to the minimum and maximumoperations and corresponding results for an interval division operationin accordance with an embodiment of the present invention.

[0037] Table 2A illustrates the steps involved in performing a minimumoperation for an interval multiplication operation in accordance with anembodiment of the present invention.

[0038] Table 2B illustrates the steps involved in performing a minimumoperation for an interval division operation in accordance with anembodiment of the present invention.

DETAILED DESCRIPTION

[0039] The following description is presented to enable any personskilled in the art to make and use the invention, and is provided in thecontext of a particular application and its requirements. Variousmodifications to the disclosed embodiments will be readily apparent tothose skilled in the art, and the general principles defined herein maybe applied to other embodiments and applications without departing fromthe spirit and scope of the present invention. Thus, the presentinvention is not intended to be limited to the embodiments shown, but isto be accorded the widest scope consistent with the principles andfeatures disclosed herein.

[0040] The data structures and code described in this detaileddescription are typically stored on a computer readable storage medium,which may be any device or medium that can store code and/or data foruse by a computer system. This includes, but is not limited to, magneticand optical storage devices such as disk drives, magnetic tape, CDs(compact discs) and DVDs (digital versatile discs or digital videodiscs), and computer instruction signals embodied in a transmissionmedium (with or without a carrier wave upon which the signals aremodulated). For example, the transmission medium may include acommunications network, such as the Internet.

[0041] Computer System

[0042]FIG. 1 illustrates a computer system 100 in accordance with anembodiment of the present invention. As illustrated in FIG. 1, computersystem 100 includes processor 102, which is coupled to a memory 112 anda peripheral bus 110 through bridge 106. Bridge 106 can generallyinclude any type of circuitry for coupling components of computer system100 together.

[0043] Processor 102 can include any type of processor, including, butnot limited to, a microprocessor, a mainframe computer, a digital signalprocessor, a personal organizer, a device controller and a computationalengine within an appliance. Processor 102 includes an arithmetic unit104, which is capable of performing computational operations usingfloating-point numbers.

[0044] Processor 102 communicates with storage device 108 through bridge106 and peripheral bus 110. Storage device 108 can include any type ofnon-volatile storage device that can be coupled to a computer system.This includes, but is not limited to, magnetic, optical, andmagneto-optical storage devices, as well as storage devices based onflash memory and/or battery-backed up memory.

[0045] Processor 102 communicates with memory 112 through bridge 106.Memory 112 can include any type of memory that can store code and datafor execution by processor 102. As illustrated in FIG. 1, memory 112contains computational code for intervals 114. Computational code 114contains instructions for the interval operations to be performed onindividual operands, or interval values 115, which are also storedwithin memory 112. This computational code 114 and these interval values115 are described in more detail below with reference to FIGS. 2-5.

[0046] Note that although the present invention is described in thecontext of computer system 100 illustrated in FIG. 1, the presentinvention can generally operate on any type of computing device that canperform computations involving floating-point numbers. Hence, thepresent invention is not limited to the computer system 100 illustratedin FIG. 1.

[0047] Compiling and Using Interval Code

[0048]FIG. 2 illustrates the process of compiling and using code forinterval computations in accordance with an embodiment of the presentinvention. The system starts with source code 202, which specifies anumber of computational operations involving intervals. Source code 202passes through compiler 204, which converts source code 202 intoexecutable code form 206 for interval computations. Processor 102retrieves executable code 206 and uses it to control the operation ofarithmetic unit 104.

[0049] Processor 102 also retrieves interval values 115 from memory 112and passes these interval values 115 through arithmetic unit 104 toproduce results 212. Results 212 can also include interval values.

[0050] Note that the term “compilation” as used in this specification isto be construed broadly to include pre-compilation and just-in-timecompilation, as well as use of an interpreter that interpretsinstructions at run-time. Hence, the term “compiler” as used in thespecification and the claims refers to pre-compilers, just-in-timecompilers and interpreters.

[0051] Arithmetic Unit for Intervals

[0052]FIG. 3 illustrates arithmetic unit 104 for interval computationsin more detail accordance with an embodiment of the present invention.Details regarding the construction of such an arithmetic unit are wellknown in the art. For example, see U.S. Pat. Nos. 5,687,106 and6,044,454, which are hereby incorporated by reference in order toprovide details on the construction of such an arithmetic unit.Arithmetic unit 104 receives intervals 302 and 312 as inputs andproduces interval 322 as an output.

[0053] In the embodiment illustrated in FIG. 3, interval 302 includes afirst floating-point number 304 representing a first endpoint ofinterval 302, and a second floating-point number 306 representing asecond endpoint of interval 302. Similarly, interval 312 includes afirst floating-point number 314 representing a first endpoint ofinterval 312, and a second floating-point number 316 representing asecond endpoint of interval 312. Also, the resulting interval 322includes a first floating-point number 324 representing a first endpointof interval 322, and a second floating-point number 326 representing asecond endpoint of interval 322.

[0054] Note that arithmetic unit 104 includes circuitry for performingthe interval operations that are outlined in FIG. 5. This circuitryenables the interval operations to be performed efficiently.

[0055] However, note that the present invention can also be applied tocomputing devices that do not include special-purpose hardware forperforming interval operations. In such computing devices, compiler 204converts interval operations into a executable code that can be executedusing standard computational hardware that is not specially designed forinterval operations.

[0056]FIG. 4 is a flow chart illustrating the process of performing aninterval computation in accordance with an embodiment of the presentinvention. The system starts by receiving a representation of aninterval, such as first floating-point number 304 and secondfloating-point number 306 (step 402). Next, the system performs anarithmetic operation using the representation of the interval to producea result (step 404). The possibilities for this arithmetic operation aredescribed in more detail below with reference to FIG. 5.

[0057] Interval Operations

[0058]FIG. 5 illustrates four different interval operations inaccordance with an embodiment of the present invention. These intervaloperations operate on the intervals X and Y. The interval X includes twoendpoints,

[0059]x denotes the lower bound of X, and

[0060] {overscore (x)} denotes the upper bound of X.

[0061] The interval X is a closed subset of the extended (including −∞and +∞) real numbers R* (see line 1 of FIG. 5). Similarly the interval Yalso has two endpoints and is a closed subset of the extended realnumbers R* (see line 2 of FIG. 5).

[0062] Note that an interval is a point or degenerate interval if X=[x,x]. Also note that the left endpoint of an interior interval is alwaysless than or equal to the right endpoint. The set of extended realnumbers, R* is the set of real numbers, R, extended with the two idealpoints negative infinity and positive infinity:

R*=R∪{−∞}∪{+∞}.

[0063] In the equations that appear in FIG. 5, the up arrows and downarrows indicate the direction of rounding in the next and subsequentoperations. Directed rounding (up or down) is applied if the result of afloating-point operation is not machine-representable.

[0064] The addition operation X+Y adds the left endpoint of X to theleft endpoint of Y and rounds down to the nearest floating-point numberto produce a resulting left endpoint, and adds the right endpoint of Xto the right endpoint of Y and rounds up to the nearest floating-pointnumber to produce a resulting right endpoint.

[0065] Similarly, the subtraction operation X−Y subtracts the rightendpoint of Y from the left endpoint of X and rounds down to produce aresulting left endpoint, and subtracts the left endpoint of Y from theright endpoint of X and rounds up to produce a resulting right endpoint.

[0066] The multiplication operation selects the minimum value of fourdifferent terms (rounded down) to produce the resulting left endpoint.These terms are: the left endpoint of X multiplied by the left endpointof Y; the left endpoint of X multiplied by the right endpoint of Y; theright endpoint of X multiplied by the left endpoint of Y; and the rightendpoint of X multiplied by the right endpoint of Y. This multiplicationoperation additionally selects the maximum of the same four terms(rounded up) to produce the resulting right endpoint.

[0067] Similarly, the division operation selects the minimum of fourdifferent terms (rounded down) to produce the resulting left endpoint.These terms are: the left endpoint of X divided by the left endpoint ofY; the left endpoint of X divided by the right endpoint of Y; the rightendpoint of X divided by the left endpoint of Y; and the right endpointof X divided by the right endpoint of Y. This division operationadditionally selects the maximum of the same four terms (rounded up) toproduce the resulting right endpoint. For the special case where theinterval Y includes zero, X/Y is an exterior interval that isnevertheless contained in the interval R*.

[0068] Note that the result of any of these interval operations is theempty interval if either of the intervals, X or Y, are the emptyinterval. Also note, that in one embodiment of the present invention,extended interval operations never cause undefined outcomes, which arereferred to as “exceptions” in the IEEE 754 standard.

[0069] Representing Intervals

[0070]FIG. 6 illustrates a scheme for representing intervals inaccordance with an embodiment of the present invention. Note that thebelow-described scheme for representing intervals can use twofloating-point numbers that adhere to the floating-point number formatspecified in the IEEE standard 754 for binary floating-point arithmetic.In this way, existing floating-point hardware and software can be used.However, note that the present invention can generally be applied to anyfloating-point representation, and is not limited to IEEE standard 754.

[0071] Also note that no additional data are required to representinfinite or empty intervals. Hence, the below-described scheme minimizesthe memory storage requirements for intervals, and thereby improvescache performance and data throughput. These improvements can greatlyimprove computational efficiency.

[0072] (1) Referring the FIG. 6, the empty interval is represented by[NaN_(Ø), NaN_(Ø)], wherein NaN_(Ø) is a non-default not-a-number (NaN).Note that IEEE standard 754 specifies a special exponent value torepresent a NaN. Note that a default NaN value can be generated as theresult of an undefined operation, such as dividing by zero, an underflowor an overflow. By varying the mantissa of the NaN, the NaN value can becustomized to be a non-default value.

[0073] (2) Next, the interval [−∞, +∞] can be represented by [−inf,+inf]. Note that IEEE standard 754 also specifies a representation forboth positive infinity (+inf) and negative infinity (−inf).

[0074] (3) Next, for two real machine-representable numbers a and b with−fp_max≦a≦−fp_min, or +fp_min≦a≦+fp_max and similarly for b, and wherea<b, the interval [a, b] is represented by [A, B], where A and B arefloating-point representations of the finite numbers a and b.

[0075] (4) Next is the case of [a, 0] where −fp_max≦a≦−fp_min (−fp_minis the closest negative floating-point number to zero). This isrepresented by [A, ±0]. Note that IEEE standard 754 specifies arepresentation for positive zero (+0) as well as negative zero (−0). Inthe simple system, this distinction is not used.

[0076] (5) Next, the interval [0, 0] is represented by [±0, ±0].

[0077] (6) Next is the case of [0, b], where +fp_min≦b≦+fp_max. This isrepresented by [±0, B].

[0078] (7) Next is the case of [−∞, b], where −fp_max≦b≦+fp_max. This isrepresented by [−inf B].

[0079] (8) Next is the case of [a, +∞], where −fp_max≦a≦+fp_max. This isrepresented by [A, +inf].

[0080] Minimum and Maximum Computations

[0081] The min-max algorithm for finite interval multiplication is:

[a,b]×[c,d]=[min(⇓ac,ad,bc,bd), max(↑ac,ad,bc,bd)].

[0082] Note that one embodiment of the present invention uses internalrepresentations that allow existing IEEE instructions to be used toproduce all the desired results, including the propagation of empty andentire intervals.

[0083] The empty interval, “Ø”, and entire interval, “R*”, propagate inexactly the same way, except with respect to each other, in which casethe empty interval dominates. Choosing “[NAN_(Ø), NaN_(Ø)]” to representØ and “[−inf,+inf]” to represent R* facilitates their propagation andinteraction. In particular, Ø×X=Ø results naturally from:

[NAN _(Ø) ,NaN _(Ø) ]×X=[NAN _(Ø) ,NaN _(Ø)]

[0084] where X is any interval, including “[−inf,+inf]”, representingR*.

[0085] The empty interval originates only when explicitly set byinterval functions or operators. Once set, Ø propagates. On the otherhand, default NaN can arise in a variety of ways, includingoperator-operand combinations, such as IEEE 754±0×±inf. By choosing thenon-default “NaN_(Ø)” to represent endpoints of Ø, control is maintainedover the occurrence of “NaN_(Ø)”. Because default NaN is temporarilyused only in “min-max” algorithms, any saved default “NaN” must be theresult of an interval implementation error or a point operation. Thisfact can be used to implement a validity test.

[0086] In one embodiment of the present invention, default NaNs can onlyarise in one different context, but it must be distinguished fromNaN_(Ø). R* propagation is represented by:

[−0,+0]×[−inf,+inf]=[−inf,+inf].

[0087] Given the R* propagation context, all four intermediate scalarproducts are default NaN. When the context is 0 propagation, all fourintermediate scalar products are NaN_(Ø).

[0088] Therefore, to separate these two contexts it is sufficient toemploy modified min and max functions having the properties shown inTable 1A (for multiplication under the simple interval system) and Table1B (for division under the simple interval system) below. TABLE 1A [a,b]× [c,d] min(NaN_(ø), NaN_(ø), NaN_(ø), NaN_(ø)) = NaN_(ø) max(NaN_(ø),NaN_(ø), NaN_(ø), NaN_(ø)) = NaN_(ø) min(NaN, NaN, NaN, NaN) = −infmax(NaN, NaN, NaN, NaN) = +inf min(X, Y, NaN, NaN) = min(X,Y) max(X, Y,NaN, NaN) = max(X,Y) ac ad bc bd min max case min(ac,ad,bc,bd)max(ac,ad,bc,bd) 1 NaN −inf +inf 2 NaN −inf +inf 3 NaN −inf +inf 4 NaN−inf +inf 5 NaN NaN −inf +inf 6 NaN NaN −inf +inf 7 NaN NaN −inf +inf 8NaN NaN −inf +inf 9 NaN NaN −inf +inf 10 NaN NaN −inf +inf 11 NaN NaNNaN NaN −inf +inf 12 NaN_(ø) NaN_(ø) NaN_(ø) NaN_(ø) NaN_(ø) NaN_(ø) 13

[0089] Table 1A contains all the possibilities for multiplication underthe simple interval system, and Table 1B contains all of thepossibilities for division. The first four columns are the four inputs,where ac, ad, bc, and bd represent the four inputs to the minimum ormaximum operation, assuming X=[a,b], Y=[c,d] are being computed. A blankinput cell means that this input value is neither NaN_(Ø) nor NaN. Thelast two columns are the returned minimum and maximum results,respectively. TABLE 1B [a,b]/[c,d] ac ad bc bd min max casemin(ac,ad,bc,bd) max(ac,ad,bc,bd) 1 NaN min(ad,bc,bd) max(ad,bc,bd) 2NaN min(ac,bc,bd) max(ac,bc,bd) 3 NaN min(ac,ad,bd) max(ac,ad,bd) 4 NaNmin(ac,ad,bc) max(ac,ad,bc) 5 NaN NaN min(ad,bd) max(ad,bd) 7 NaN NaNmin(ac,bc) max(ac,bc) 10 NaN_(ø) NaN_(ø) NaN_(ø) NaN_(ø) NaN_(ø) NaN_(ø)13

[0090] Table 1A contains all the possibilities for multiplication underthe simple interval system, and Table 1B contains all of thepossibilities for division. The first four columns are the four inputs,where ac, ad, bc, and bd represent the four inputs to the minimum ormaximum operation, assuming X=[a,b], Y=[c,d] are being computed. A blankinput cell means that this input value is neither NaN_(Ø) nor NaN. Thelast two columns are the returned minimum and maximum results,respectively.

[0091] Min and Max Instructions

[0092] To understand the methods to compute a minimum and a maximum, itis helpful to examine the possible arguments to the minimum and maximumoperations. (See Table 2A for multiplication under the simple system andTable 2B for division under the simple system below.) Note that thevariables ac, ad, bc and ad can be the result of individual operandmultiplications or divisions depending on the operation being performed.TABLE 2A Input: ac,ad,bc,bd Output: “Simple”minimum for multiplicationif ac==NaNø,   return NaNø, {case 13} if ac==NaN or ad==NaN or bc==NaNor bd==NaN   return −inf  {cases 2 through 12} endif returnmin(ac,ad,bc,bd) end

[0093] Table 2A (above) contains the min algorithm for multiplicationunder the simple system. The max algorithm is exactly the same as themin algorithm except: (1) min is replaced by max everywhere in thealgorithm; and (2) the sign of −inf is reversed to +inf in cases 2-12.

[0094] Table 2B (below) contains the min algorithm for division underthe simple system. The max algorithm is exactly the same as the minalgorithm except: (1) min is replaced by max everywhere in thealgorithm; and (2) each instance of fp_max is replaced by fp_min.

[0095] Note that the min-max version of division requires the additionof a test to check for divisors that contain zero, in which case R* isreturned, provided the numerator is not empty.

[0096] Also, note that the methods outlined in Tables 2A and 2B aresuitable for efficient implementation in hardware as well as insoftware.

[0097] The foregoing descriptions of embodiments of the presentinvention have been presented for purposes of illustration anddescription only. They are not intended to be exhaustive or to limit thepresent invention to the forms disclosed. Accordingly, manymodifications and variations will be apparent to practitioners skilledin the art. For example, in the method outlined in Table 2, the order ofthe input operands, a, b, c, and d, can be permuted to produce anequivalent min/max operation. The present invention covers all suchpermutations. TABLE 2B Input: ac=a/c, ad=a/d, bc=b/c, bd=b/d Output:“Simple” minimum for division if ac==NaNø  return NaNø {case 13} ifac==NaN  ac = fp_max {cases 2 & 7} endif if ad==NaN  ad = fp_max {cases3 & 10} endif if bc==NaN  bc = fp_max {cases 4 & 7} endif if bd==NaN  bd= fp_max {cases 5 & 10} endif return min(ac,ad,bc,bd) end

[0098] Additionally, the above disclosure is not intended to limit thepresent invention. The scope of the present invention is defined by theappended claims.

1-10 (Canceled).
 11. A method for performing extremum computation for aninterval division operation, comprising: receiving at least fourfloating-point numbers, including a first floating-point number, asecond floating-point number, a third floating-point number and a fourthfloating-point number; and computing a minimum of the at least fourfloating-point numbers, wherein computing the minimum includes computingthe minimum in an arithmetic unit for intervals; wherein if the at leastfour floating-point numbers include one or more default NaN(not-a-number) values, the default NaN values are ignored in computingthe minimum.
 12. The method of claim 11, wherein the minimum is a leftendpoint of a resulting interval from the interval division operation;wherein the first floating-point number is the result of a divisionoperation between the left endpoint of a first interval and the leftendpoint of a second interval; wherein the second floating-point numberis the result of a division operation between the left endpoint of thefirst interval and the right endpoint of the second interval; whereinthe third floating-point number is the result of a division operationbetween the right endpoint of the first interval and the left endpointof the second interval; and wherein the fourth floating-point number isthe result of a division operation between the right endpoint of thefirst interval and the right endpoint of the second interval.
 13. Themethod of claim 12, wherein computing the minimum involves setting theminimum to negative infinity, if the second interval contains zero. 14.The method of claim 11, wherein computing the minimum involves settingthe minimum to a value representing the empty interval, if any of the atleast four floating-point numbers contain the value representing theempty interval.
 15. The method of claim 14, wherein the valuerepresenting the empty interval is a non-default NaN value.
 16. Themethod of claim 11, wherein if none of the at least four floating-pointnumbers is a default NaN value or a value representing the emptyinterval, computing the minimum involves selecting the minimum of the atleast four floating-point numbers.
 17. The method of claim 11, furthercomprising: computing a maximum of the at least four floating-pointnumbers; wherein if the at least four floating-point numbers include oneor more default NaN (not-a-number) values, the default NaN values areignored in computing the maximum.
 18. The method of claim 17, whereinthe maximum is a right endpoint of a resulting interval from theinterval division operation; wherein the first floating-point number isthe result of a division operation between the left endpoint of a firstinterval and the left endpoint of a second interval; wherein the secondfloating-point number is the result of a division operation between theleft endpoint of the first interval and the right endpoint of the secondinterval; wherein the third floating-point number is the result of adivision operation between the right endpoint of the first interval andthe left endpoint of the second interval; and wherein the fourthfloating-point number is the result of a division operation between theright endpoint of the first interval and the right endpoint of thesecond interval.
 19. The method of claim 18, wherein computing themaximum involves setting the maximum to positive infinity, if the secondinterval contains zero.
 20. The method of claim 17, wherein computingthe maximum involves setting the maximum to a value representing theempty interval, if any of the at least four floating-point numberscontain the value representing the empty interval.
 21. The method ofclaim 20, wherein the value representing the empty interval is anon-default NaN value.
 22. The method of claim 17, wherein if none ofthe at least four floating-point numbers is a default NaN value or avalue representing the empty interval, computing the maximum involvesselecting the maximum of the at least four floating-point numbers. 23-32(Canceled).
 33. A computer-readable storage medium storing instructionsthat when executed by a computer cause the computer to perform a methodfor performing extremum computation for an interval division operation,the method comprising: receiving at least four floating-point numbers,including a first floating-point number, a second floating-point number,a third floating-point number and a fourth floating-point number; andcomputing a minimum of the at least four floating-point numbers; whereinif the at least four floating-point numbers include one or more defaultNaN (not-a-number) values, the default NaN values are ignored incomputing the minimum.
 34. The computer-readable storage medium of claim33, wherein the minimum is a left endpoint of a resulting interval fromthe interval division operation; wherein the first floating-point numberis the result of a division operation between the left endpoint of afirst interval and the left endpoint of a second interval; wherein thesecond floating-point number is the result of a division operationbetween the left endpoint of the first interval and the right endpointof the second interval; wherein the third floating-point number is theresult of a division operation between the right endpoint of the firstinterval and the left endpoint of the second interval; and wherein thefourth floating-point number is the result of a division operationbetween the right endpoint of the first interval and the right endpointof the second interval.
 35. The computer-readable storage medium ofclaim 34, wherein computing the minimum involves setting the minimum tonegative infinity, if the second interval contains zero.
 36. Thecomputer-readable storage medium of claim 33, wherein computing theminimum involves setting the minimum to a value representing the emptyinterval, if any of the at least four floating-point numbers contain thevalue representing the empty interval.
 37. The computer-readable storagemedium of claim 36, wherein the value representing the empty interval isa non-default NaN value.
 38. The computer-readable storage medium ofclaim 33, wherein if none of the at least four floating-point numbers isa default NaN value or a value representing the empty interval,computing the minimum involves selecting the minimum of the at leastfour floating-point numbers.
 39. The computer-readable storage medium ofclaim 33, the method further comprising: computing a maximum of the atleast four floating-point numbers; wherein if the at least fourfloating-point numbers include one or more default NaN (not-a-number)values, the default NaN values are ignored in computing the maximum. 40.The computer-readable storage medium of claim 39, wherein the maximum isa right endpoint of a resulting interval from the interval divisionoperation; wherein the first floating-point number is the result of adivision operation between the left endpoint of a first interval and theleft endpoint of a second interval; wherein the second floating-pointnumber is the result of a division operation between the left endpointof the first interval and the right endpoint of the second interval;wherein the third floating-point number is the result of a divisionoperation between the right endpoint of the first interval and the leftendpoint of the second interval; and wherein the fourth floating-pointnumber is the result of a division operation between the right endpointof the first interval and the right endpoint of the second interval. 41.The computer-readable storage medium of claim 40, wherein computing themaximum involves setting the maximum to positive infinity, if the secondinterval contains zero.
 42. The computer-readable storage medium ofclaim 39, wherein computing the maximum involves setting the maximum toa value representing the empty interval, if any of the at least fourfloating-point numbers contain the value representing the emptyinterval.
 43. The computer-readable storage medium of claim 42, whereinthe value representing the empty interval is a non-default NaN value.44. The computer-readable storage medium of claim 39, wherein if none ofthe at least four floating-point numbers is a default NaN value or avalue representing the empty interval, computing the maximum involvesselecting the maximum of the at least four floating-point numbers. 45-54(Canceled).
 55. An apparatus that performs extremum computation for aninterval division operation, comprising: an input that is configured toreceive at least four floating-point numbers, including a firstfloating-point number, a second floating-point number, a thirdfloating-point number and a fourth floating-point number; and acomputing mechanism that is configured to compute a minimum of the atleast four floating-point numbers; wherein if the at least fourfloating-point numbers include one or more default NaN (not-a-number)values, the default NaN values are ignored in computing the minimum. 56.The apparatus of claim 55, wherein the minimum is a left endpoint of aresulting interval from the interval division operation; wherein thefirst floating-point number is the result of a division operationbetween the left endpoint of a first interval and the left endpoint of asecond interval; wherein the second floating-point number is the resultof a division operation between the left endpoint of the first intervaland the right endpoint of the second interval; wherein the thirdfloating-point number is the result of a division operation between theright endpoint of the first interval and the left endpoint of the secondinterval; and wherein the fourth floating-point number is the result ofa division operation between the right endpoint of the first intervaland the right endpoint of the second interval.
 57. The apparatus ofclaim 56, wherein if the second interval contains zero, the computingmechanism is configured to set the minimum to negative infinity.
 58. Theapparatus of claim 55, wherein the computing mechanism is configured toset the minimum to a value representing the empty interval, if any ofthe at least four floating-point numbers contain the value representingthe empty interval.
 59. The apparatus of claim 58, wherein the valuerepresenting the empty interval is a non-default NaN value.
 60. Theapparatus of claim 55, wherein if none of the at least fourfloating-point numbers is a default NaN value or a value representingthe empty interval, the computing mechanism is configured to select theminimum of the at least four floating-point numbers.
 61. The apparatusof claim 55 wherein: the input is further configured to receive at leastfour floating-point numbers, including a first floating-point number, asecond floating-point number, a third floating-point number and a fourthfloating-point number; the computing mechanism is further configured tocompute a maximum of the at least four floating-point numbers; and ifthe at least four floating-point numbers include one or more default NaN(not-a-number) values, the default NaN values are ignored in computingthe maximum.
 62. The apparatus of claim 61, wherein the maximum is aright endpoint of a resulting interval from the interval divisionoperation; wherein the first floating-point number is the result of adivision operation between the left endpoint of a first interval and theleft endpoint of a second interval; wherein the second floating-pointnumber is the result of a division operation between the left endpointof the first interval and the right endpoint of the second interval;wherein the third floating-point number is the result of a divisionoperation between the right endpoint of the first interval and the leftendpoint of the second interval; and wherein the fourth floating-pointnumber is the result of a division operation between the right endpointof the first interval and the right endpoint of the second interval. 63.The apparatus of claim 62, wherein if the second interval contains zero,the computing mechanism is configured to set the maximum to positiveinfinity.
 64. The apparatus of claim 61, wherein the computing mechanismis configured to set the maximum to a value representing the emptyinterval, if any of the at least four floating-point numbers contain thevalue representing the empty interval.
 65. The apparatus of claim 64,wherein the value representing the empty interval is a non-default NaNvalue.
 66. The apparatus of claim 61, wherein if none of the at leastfour floating-point numbers is a default NaN value or a valuerepresenting the empty interval, the computing mechanism is configuredto select the maximum of the at least four floating-point numbers.